Earth Observation With Satellite

How successfully do rain gauges catch rainfall patterns? Do the
satellites record the same patterns of data as the ground-based gauges?
How many gauges are required in order to observe regional patterns in
rainfall? Scientists compare measurements from rain gauges with
satellite measurements to answer these and other related questions. By
increasing the number of rain gauge measurements, citizen scientists can
help increase the overall accuracy and precision of space-based
precipitation monitoring. Using the June 2008 Midwest flood event, this
section illustrates how to explore satellite data and rain gauge data
together to answer questions about regional rainfall.

For this example, we are going to use a station in Monroe County, in
south-central Indiana. The station, near Indianapolis, Indiana, received
a record-breaking period of rainfall from June 2–12, 2008. This
extreme rainfall event subsequently caused intense flooding in the Ohio
and Lower Mississippi watersheds.

Part 1. Observer (Ground-based) Data

How to find a station of interest in CoCoRaHS.

Step 1. Access the map of the area that you are interested in.

Launch the CoCoRaHS website

Once the site has loaded, click on the
word, “maps”.

Once the daily maps page loads, select the “Station
Number Maps” link from the list of map types. (last
one in the list)

Under map location title, use the pull down menu to
select “stations,” choose your state of
interest. In this case, choose Indiana.

Next choose the “county,” Monroe. Leave the
dates and map colors in their default settings.

Click the button, “Get Map”.

A map window will open with stations shown as little dots with
their ID numbers next to them. We will use this station location map
for reference later, so save it in the background or on your
desktop.

Step 2. Acquire Precipitation data from CoCoRaHS

Open a new window in your browser with the CoCoRaHS home page
again.

This time on the top tab bar, click on, “view
data”.

A new page will load. On this page there will be a list of
station types. Scroll most of the way down the list to the
link “List Stations”. This is a list of stations by
state and county. Click on this link.

On the next page, choose the state and county you are interested
in. For this example choose, Indiana and Monroe County. click
search. There are many stations in Indiana, this will select only
the 15 stations that are in Monroe County. The stations are listed
by; state, county and ID number. In the table of stations, under
the “view” heading, click on the magnifying glass in the
row with “IN-MN-14” to learn more about this station‘s
detailed location, including its latitude and longitude.

Record this station‘s latitude and longitude to use later
in the comparison with satellite data. (Record the following:
Station IN-MN-14, Latitude 39.265964, Longitude -86.521293.)
Optional: click view the station in Google Maps.

In the next page that loads, you can type in the station ID
numbers of any three stations that are of interest. Use the saved
map of stations from step 3 of part 1 to view the station
locations.

Type in IN-MN-14, IN-MG-14, and IN-MN-3. Choose the dates
6-02-2008 and 6-12-2008 as your beginning and end dates. Click
the “get summary” button.

You will get a table of data. Check the data to see that
it makes sense—is it what you asked for?

Look for any days of intense precipitation. In this case,
there was a rainy period from approximately June 1 -15,
2008. What date did the rainfall amount peak? How do the
stations vary?

Once you have checked the data, copy and paste the station‘s
data from the CoCoRaHS site into a spreadsheet program such as
excel.

Since satellites report rain rate in millimeters per hour it will
be easier to compare results if you use excel to convert the data
from inches to millimeters by multiplying the total by 25.4. (1
inch=25.4 mm)

Produce a graph of rainfall rate in millimeters per 24 hours (y
axis) versus date (x axis). Save your graph for comparison with the
graph of satellite data that you will produce in the part 2.

Part 2: Above and Below

Comparing CoCoRaHS data with NASA Satellite data from the same location
and time period. This example uses the 3-hourly TRMM and Other Rainfall
Estimate (3B42 V6).

The Tropical Rainfall Measuring Mission (TRMM, pronounced “trim”)
satellite is the most accurate rainfall observing satellite to orbit the
Earth. It carries a suite of five instruments that, when combined, allow
scientists to gather a very detailed three-dimensional view of rainfall
patterns. However, these instruments do not directly measure
precipitation. Instead they use a combination of active radar and
passive measurements to record the energy and water vapor flowing
through the atmosphere. This data allows scientist to estimate
precipitation patterns on large scales across the Earth. One instrument
is “passive,” observing the intensity of radiant energy that
the atmosphere, land, and ocean emit into space at microwave
frequencies. The other instrument is the first weather radar in space,
recording vertical profiles of rain, similar to surface-based radar
systems.

Together, these data sets allow scientists to build a 3-D picture of
rainfall patterns in space and time. These estimates are calibrated by
comparing the results to ground based observations, such as rain gauges
and radars, with the satellite data. By increasing the number of rain
gauge measurements scientists will be able to increase the overall
accuracy and precision of precipitation monitoring.

To complete the comparison of satellite and rain-gauge data, use the
dates, and location of your the selected CoCoRaHS stations as a starting
point for a comparison of satellite and observer data.

Step 1. Compare time series data from several rain gauges with that from
the Satellites.

When this page loads, you will see a map of the world. Use your
cursor to draw a box around your area of interest, Indiana. Note
what latitudes and longitudes are automatically input into the boxes
below the map. Optional: Try drawing several boxes on the map in
order to better understand the latitude and longitude numbers.

Alternately, use the coordinates that you recorded in part 1 step
3, from the Monroe, Indiana CoCoRaHS observers site as a starting
point.

They were Station IN-MN-14 Latitude 39.265964, Longitude
-86.521293

In Giovanni choose coordinates that will give you a tight box
around this area such as: -88 West, 42 North, 37.5 South , -84.5
East.

Choose “precipitation” as the parameter, set the
temporal dates to begin June 2, 2008, and end June 12, 2008, and the
visualization as “time series”.

Click the “generate visualization” button at the
bottom of the page.

A new page will appear, showing you the steps the program is
executing to generate the results. After a few seconds, when the
processing is complete, you will see a graph.

Note: the graph will show you rain rates as observed
by the satellite. A rain rate is a measurement of how hard it
was raining. By contrast, your gauge measures rainfall totals,
the amount of rain that fell in a 24-hour period. In theory, the
rain rate multiplied by 24 should match the 24-hour rainfall
total. In practice, however, this is seldom true because rain
does not fall at the same rate over 24 hours.

Compare the graph of the satellite data to a graph of the
CoCoRaHS data from Stations IN-MN-14 and IN-MG-14 during the same
time period. Note that the gauges both recorded a large amount of
rain on the same date that the satellites recorded a heavy rainfall
rate.

Step 2. Mapping the Satellite Data.

While rate versus time is one way to analyze data for several gauges, a
broader way to look at rainfall rates across a larger area is on a map.
In this example you will plot rainfall rates for this time period on a
map for the area. The resulting map will help you to understand where
the rainfall was the greatest, allowing you to relate this information
to other geographic information such as topographic features and urban
areas. In this example, we are going use the rain gauge and TOVAS
satellite data for the state of Indiana.

Use the map to predict in which watersheds the floods would have
occurred. How might you, as a local weather personality or hydrologist
have advised the citizens living this region? Would you have encouraged
citizens living downstream of Indianapolis to evacuate? Read more about
this flooding event at an online news source such as msnbc or cbs
online.

You can broaden your understanding of the event using Giovanni to further
analyze the satellite data.

Some other interesting visualizations that can be done in Giovanni:

Choose “animation” to see the amount of rain each day
for the period linked together in a quick time movie.

Choose “Scatter plot” to plot rainfall data versus
error to see the relationship between rainfall rate and error. The
greater the rate the greater the error.

Return to the TRMM site and choose the monthly averages. Choose
the “anomaly plot” for the two-year period between
January 2007 and December 2008. “Animate” the monthly
averages.

Going Further

Other groups also collect precipitation data, which may be used in a
comparison with satellite data. These groups include:

If you are interested in studying rainfall patterns in Arizona, you can
map gauge data from Rainlog and satellite data in Google Earth. Both
Giovanni and Rainlog will allow you to download a Google Earth file. By
layering the two files in Google Earth, you can compare rainfall
patterns.